1. Field of the Invention
The present invention relates to a wireless communication system, and more particularly, to a method and apparatus for transmitting and receiving signals based on dual compressive sensing in a wireless communication system.
2. Discussion of the Related Art
A wireless Sensor Network (WSN) refers to a system for obtaining various information from a plurality of sensor nodes. In recent years, with an increase in sensor nodes and an increase in the amount of observed information, questions about high-dimensional signal processing have been raised and studies thereon has increased. To solve an increase of communication traffic caused by the occurrence of a high-dimensional signal in the WSN, research has been conducted into a distributed compression method, such as entropy coding (see R. Cristescu, B. Beferull-Lozano, M. Vetterli, and R. Wattenhofer, “Network correlated data gathering with explict communication,” IEEE/ACM Trans. On Networking, 14(1):41-54, February 2006, hereinafter, referred to as Reference 1) and Slepian-Wolf coding (see D. Slepian and J. K. Wolf, “Noiseless coding of correlated information sources,” 19:471-480, July 1973, hereinafter, referred to as Reference 2). However, conventional distributed compression technologies are disadvantageous in that information such as a correlation between information acquired by distributed nodes should be known in advance in order to perform compression. In addition, since sensor nodes of the WSN that require low complexity are required to process high operation throughput, it is not appropriate to actually apply the conventional distributed compression technologies.
Compressive sensing refers to a scheme of converting a high-dimensional signal into a low-dimensional signal so that an observed, or stored and compressed signal can be recovered into an original high-dimensional signal with high probability. Recently, compressive sensing has been studied in a variety of fields. For basic theory about compressive sensing, reference may be made to D. Donoho, “Compressive Sensing,” IEEE Trans. Inform. Theory, vol. 52, no. 4, pp. 1289-1306, April 2005 (hereinafter, referred to as Reference 3).
Compressive sensing has drawn attention, due to a few unique characteristics, as a future technology capable of solving problems in the WSN having a plurality of sensor nodes and a large amount of information. The biggest advantage of compressive sensing in the WSN is that it is easy to perform distributed compression. As opposed to conventional distributed compression schemes such as entropy coding and Slepian-Wolf coding, a compressive sensing technique has been greatly spotlighted as a future technique for high-dimensional signal processing of the WSN because distributed compression can be performed through a simple linear operation without previously receiving additional information in a compression process (see C. Luo, F. Wu, J. Sun and C. W. Chen, “Compressive data gathering for large scale wireless sensor networks,” Mobicom '09, September 2009, hereinafter, referred to as Reference 4). However, research into a WSN to which compressive sensing is applied are still in an early stage and various in-depth studies have not been carried out.